Traditionally, a data store in a distributed computing environment relies on expensive batteries to provide durability to volatile memory caches. Therefore, when a power failure occurs, data received by the data store that has yet to be committed to a non-volatile memory store may be maintained, through the use of batteries or other power back-up, until the data has been committed. However, the reliance on back-up power and/or batteries increases the complexity and cost of a data store. Additionally, in a distributed computing environment where multiple copies of data are expected to be committed to different data stores before a commitment of the data is acknowledged, a consistent write time is difficult to attain because of variations in data store resources when the data is committed in a non-sequential manner. Additionally, variations to write times may result from different data streams being written to a common data store. Therefore, optimization of data storage in a distributed computing environment is difficult to obtain because of inconsistent latency times with non-sequential storage.